Skip to content

Latest commit

 

History

History
161 lines (117 loc) · 6.9 KB

File metadata and controls

161 lines (117 loc) · 6.9 KB

PyData 2016 - Amsterdam

Presentations

The PyData map: Presenting a map of the landscape of PyData tools (Peader Coyle)
https://www.youtube.com/watch?v=QgjkgNVXSjQ
http://bit.ly/pydatakeynotespringcoil
https://peadarcoyle.wordpress.com/2016/03/02/a-map-of-the-pydata-stack/

  • Get on board with Python 3!
  • The PyData Stack comments ...
  • pandas assign - create a new column, e.g., df.assign(ln_A_plus_1=lambda x: np.log(x.A)+1)
  • xarray - Labeled heterogenous data (numpy arrays plus labels), e.g., weather forecasting data
  • blaze - Query data on different storage systems
  • bcolz - Columnar data store, high-performance compression, in- and out-of-memory operations [tabular]
  • dask - Out-of-memory calculations (usually good 10 Gb to 1 Tb) [array]
  • Arrow / Ibis - Better SQL integration with pandas API and better columnar data structures for dealing with HDFS, etc.
  • spaCy - NLP
  • Itertools
  • http://jmduke.com/posts/a-gentle-introduction-to-itertools

The Duct Tape of Heroes Bayesian statistics (Vincent D Warmerdam)
https://www.youtube.com/watch?v=dE5j6NW-Kzg
http://koaning.io/theme/notebooks/bayes.pdf

Building a live face recognition system in the blink of a very slow eye (Rodrigo Agundez)
https://www.youtube.com/watch?v=MDaZtJPv3Ik

CART: Not only Classification and Regression Trees (Marc Garcia)
https://www.youtube.com/watch?v=7fquVe4Q4No

Margaret Mahan (Store and manage data effortlessly with HDF5)
https://www.youtube.com/watch?v=XdksDmNsZ1Q

Tools and Tricks from a Pragmatic Data Scientist (Lucas Bernardi)
https://www.youtube.com/watch?v=HS7mObQttxU

Realtime Bayesian A-B testing with Spark Streaming (Dennis Bohle, Ben Teeuwen)
https://www.youtube.com/watch?v=GFcFNccbDM8

Pandas: from bdate_range to wide_to_long (Giovanni Lanzani)
https://www.youtube.com/watch?v=1NM7iPA-SMY
https://gist.github.com/gglanzani/2958fb4237083aecae8c

Python tools for webscraping (José Manuel Ortega)
https://www.youtube.com/watch?v=nDP99hYqAiI
https://github.com/PyDataMadrid2016/Conference-Info

A Hitchhiker's Guide to Data Science (Christine Doig)
https://www.youtube.com/watch?v=u3JJsoBpRYk
https://github.com/PyDataMadrid2016/Conference-Info

Understanding Random Forests (Marc García)
https://www.youtube.com/watch?v=mtIePLVqVhA

Embrace conda packages (Juan Luís Cano Rodríguez)
https://www.youtube.com/watch?v=0FnXvTaqiOo

New Computer Trends and How This Affects Us (Francesc Alted)
https://www.youtube.com/watch?v=By8xlYOCwws

Reinforcement Learning in Python (Nathan Epstein)
https://www.youtube.com/watch?v=rTMa04TZ_MY

The Future of NumPy Indexing (Jaime Fernández)
https://www.youtube.com/watch?v=o0EacbIbf58

Modelling a text corpus using Deep Boltzmann Machines (Ricardo Pio Monti)
https://www.youtube.com/watch?v=uju4RXEniA8

10 things I learned about writing data pipelines in Python and Spark (Ali Zaidi)
https://www.youtube.com/watch?v=I21_sZHjfkE

Iterables and Iterators: Going Loopy With Python (Steve Holden)
https://www.youtube.com/watch?v=iTwrF1DofCY

Building Data Pipelines in Python (Marco Bonzanini)
https://www.youtube.com/watch?v=GUI-gAPh9sU
https://speakerdeck.com/marcobonzanini/building-data-pipelines-in-python-pydata-london-2016

Probablistic Programming Data Science with PyMC3 (Thomas Wiecki)
https://www.youtube.com/watch?v=coEVZNg_nlA

KEYNOTE: Scaling Out PyData (Travis Oliphant)
https://www.youtube.com/watch?v=-aFTKM3nmZo
http://www.slideshare.net/teoliphant/scaling-pydata-up-and-out

Irregular time series and how to whip them (Aileen Nielsen)
https://www.youtube.com/watch?v=E4NMZyfao2c
https://slack-files.com/T0LFE6T6J-F17Q90AC9-b3eabe5c42

Modelling a text corpus using Deep Boltzmann Machines in python (Ricardo Pio Monti)
https://www.youtube.com/watch?v=d14RtvWvpLo
https://github.com/piomonti/DeepTextMining/blob/master/PyData%20London%20Slides.pdf
https://github.com/piomonti/DeepTextMining

Deep Learning for QSAR (Rich Lewis)
https://www.youtube.com/watch?v=kInLYwitfFs

Survival Analysis in Python and R (Linda Uruchurtu)
https://www.youtube.com/watch?v=fli-yE5grtY
https://speakerdeck.com/lindauruchurtu/survival-analysis-in-r-and-python

PySpark in Practice (Ronert Obst & Dat Tran)
https://www.youtube.com/watch?v=SETpipUZ_Lc
http://pydata2016.cfapps.io/
https://github.com/datitran/spark-tdd-example

Interactive Visualization in Jupyter with Bqplot and Interactive Widgets (Sylvain Corlay)
https://www.youtube.com/watch?v=eVET9IYgbao
https://github.com/SylvainCorlay/tutorial

Bayesianism and Survival Analysis (Jake Coltman & Jacob Goodwin)
https://www.youtube.com/watch?v=jlz2_hjW3UE

bandicoot: a toolbox to analyze mobile phone metadata (Luc Rocher)
https://www.youtube.com/watch?v=_Fb7ttS43GE
https://github.com/cynddl/pydata-london-2016

What's new in High Performance Python (Graham Markall)
https://www.youtube.com/watch?v=-5NUMvkYBNY
http://gmarkall.github.io/tutorials/pydata-london-2016/#1
https://github.com/gmarkall/tutorials/tree/master/pydata-london-2016/

Hierarchical Bayesian Modelling with PyMC3 and PySTAN (Jonathan Sedar)
https://www.youtube.com/watch?v=Jb9eklfbDyg
https://github.com/jonsedar/pymc3_vs_pystan

Christian Hennig (Assessing the quality of a clustering)
https://www.youtube.com/watch?v=Mf6MqIS2ql4
http://www.slideshare.net/PyData/christian-henning-assessing-the-quality-of-a-clustering

Finding needles in haystacks with Deep Neural Networks (Calvin Giles)
https://www.youtube.com/watch?v=bV1w_Q2Ihh4
http://www.slideshare.net/CalvinGiles/finding-needles-in-haystacks-with-deep-neural-networks

Tutorials

Deep learning tutorial - advanced techniques (Geoffrey French)
https://www.youtube.com/watch?v=2Y7mw7Mv0TI
https://speakerdeck.com/britefury/deep-learning-tutorial-advanced-techniques-pydata-london-2016
https://github.com/Britefury/deep-learning-tutorial-pydata2016

Lies damned lies and statistics in Python (Peadar Coyle)
https://www.youtube.com/watch?v=YUh46N-SZ34

Introduction to Deep Learning & Natural Language Processing (Raghotham Sripadraj & Nischal HP)
https://www.youtube.com/watch?v=BkbtYgwXsWE
https://speakerdeck.com/bargava/introduction-to-deep-learning
https://github.com/rouseguy/intro2deeplearning/

Bokeh for Data Applications and Visualization (Bryan Van de Ven)
https://www.youtube.com/watch?v=h0y90MyGo-c

Pandas from the inside (Stephen Simmons)
https://www.youtube.com/watch?v=Dr3Hv7aUkmU
https://github.com/SteveSimmons/PyData-PandasFromTheInside/blob/master/pfi.pdf
https://github.com/SteveSimmons/PyData-PandasFromTheInside